Urbanization fosters functional diversification across different districts or sections within a city or other area. For example, as a city develops, the formation of educational districts, business districts, and residential districts occurs. These districts, which are spread across the city, make up functional groups because each serves a different primary function for serving the people that live in the city. Whether they were designed by urban planners, or naturally formed during the course of urbanization, these functional groups will continue to evolve as lifestyles change and as a city continues to grow.
Discovering functional groups can enable a variety of valuable applications. For example, it can serve as a valuable organizational framework to give people a quick understanding of a complex area (e.g., New York City, Tokyo, Paris, etc.), which leads to useful applications such as social recommendations, travel planning, and the like. Both local citizens and visitors may find such information useful in navigating a city. In addition, urban planners can also use information about functional groups for calibrating urban planning as a form of feedback mechanism that allows for adjustments to be made in future urban planning of cities that do not develop quite as planned. Entrepreneurs and business owners can also leverage information about functional groups for choosing a location for a new business, and/or choosing where to advertise for their business. For example, a location's a distance from a district having a particular function (e.g., residential districts) may be a factor in choosing the location for a business.
The task of discovering functional groups is not a trivial endeavor. Prior attempts have considered information about an area in isolation to infer the functionality of districts or sections within the area. For instance, points of interest (POIs) may be indicative of the function of a district, but they are not sufficient when considered in isolation due to the compound functional nature of districts that often comprise a variety of different POIs (e.g., restaurants, universities, historical sites, etc.). Accordingly, current techniques for discovering functional groups are insufficient for the aforementioned applications.